facebookresearch / DeepSDF
Learning Continuous Signed Distance Functions for Shape Representation
Summary
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| Main Code: 2,575 LOC (19 files) = PY (60%) + CPP (37%) + H (1%) Secondary code: Test: 0 LOC (0); Generated: 0 LOC (0); Build & Deploy: 0 LOC (0); Other: 16,013 LOC (18); |
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| Duplication: 18% | |||
| File Size: 0% long (>1000 LOC), 41% short (<= 200 LOC) | |||
| Unit Size: 32% long (>100 LOC), 22% short (<= 10 LOC) | |||
| Conditional Complexity: 0% complex (McCabe index > 50), 38% simple (McCabe index <= 5) | |||
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Logical Component Decomposition: primary (5 components) | ||
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2 years, 6 months old
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0% of code updated more than 50 times Also see temporal dependencies for files frequently changed in same commits. |
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| Goals: Keep the system simple and easy to change (4) | |||
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Features of interest:
TODOs
3 files |
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Latest commit date: 2019-10-28
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